Research on the cognitive neural mechanism of privacy empowerment illusion cues regarding comprehensibility and interpretability for privacy disclosures

Abstract

Abstract In the era of artificial intelligence, privacy empowerment illusion has become a crucial means for digital enterprises and platforms to “manipulate” users and create an illusion of control. This topic has also become an urgent and pressing concern for current research. However, the existing studies are limited in terms of their perspectives and methodologies, making it challenging to fully explain why users express concerns about privacy empowerment illusion but repeatedly disclose their personal information. This study combines the associative-propositional evaluation model (APE) and cognitive load theory, using event-related potential (ERP) technology to investigate the underlying mechanisms of how the comprehensibility and interpretability of privacy empowerment illusion cues affect users’ immediate attitudes and privacy disclosure behaviours; these mechanisms are mediated by psychological processing and cognitive load differences. Behavioural research results indicate that in the context of privacy empowerment illusion cues with low comprehensibility, users are more inclined to disclose their private information when faced with high interpretability than they are when faced with low interpretability. EEG results show that in the context of privacy empowerment illusion cues with low comprehensibility, high interpretability induces greater P2 amplitudes than does low interpretability; low interpretability induces greater N2 amplitudes than does high interpretability. This study extends the scopes of the APE model and cognitive load theory in the field of privacy research, providing new insights into privacy attitudes. Doing so offers a valuable framework through which digital enterprises can gain a deeper understanding of users’ genuine privacy attitudes and immediate reactions under privacy empowerment illusion situations. This understanding can help increase user privacy protection and improve their overall online experience, making it highly relevant and beneficial.